Consulting R&D Engineer

Role Overview

We are seeking a highly experienced Consulting R&D Engineer specializing in solver-based simulation and AI-driven surrogate modeling across CFD, FEA, and Multiphysics domains. The consultant will support R&D teams, product engineering groups, and innovation programs by delivering advanced simulations, developing customized

computational workflows, and enabling accelerated virtual prototyping through AI/ML-based modeling.

This role is ideal for an expert who thrives in flexible, project-driven environments and can contribute both technically and strategically.

Key Responsibilities

• Provide specialized consulting services in CFD, FEA, and Multiphysics simulations across diverse industrial applications.
• Execute solver-based analyses including fluid flow, heat transfer, structural, multiphase, nonlinear, and coupled physics problems.
• Develop and deploy AI/ML surrogate models , reduced-order models (ROM), and digital twin components to accelerate simulation cycles.
• Design efficient simulation workflows , including meshing, boundary condition setup, solver selection, and convergence strategies.
• Build custom scripts and workflow automation using Python, MATLAB, or C++ , integrating simulation and AI pipelines.
• Interpret complex simulation data, generate actionable insights, and recommend design improvements to client teams.
• Engage with R&D, design, and product engineering stakeholders to understand requirements and propose optimized simulation strategies.
• Support HPC execution of large-scale simulations and guide clients on cluster utilization and solver performance optimization.
• Validate models using experimental or historical data and calibrate surrogate models for accuracy and robustness.
• Deliver technical reports, presentations, and advisory input to client leadership and engineering teams.
• Provide training, mentoring, or capability-building sessions for client teams on simulation methods, tools, and AI/ML applications.

Required Qualifications

• Bachelor's degree in Mechanical, Aerospace, Chemical, Materials, Civil Engineering, or related fields.
• Strong background in fluid mechanics, structural mechanics, heat transfer, and numerical methods .
• Expertise in major CFD tools:

• ANSYS Fluent, CFX, STAR-CCM+, OpenFOAM, COMSOL

• Expertise in major FEA tools:

• ANSYS Mechanical, Abaqus, LS-DYNA, NASTRAN, COMSOL

• Proven experience executing complex simulations independently with minimal guidance.

• Strong programming experience in Python (required) , with exposure to C++/MATLAB for algorithm development.
• Knowledge of discretization schemes, turbulence models, nonlinear FEM, multiphase physics, and solver stability.

Preferred Qualifications (Consulting-Oriented)

• Master's degree or PhD in Computational Mechanics, CFD, Applied Mathematics, or related advanced fields.
• Experience building and deploying ML/AI models for:
• Surrogate modeling
• ROM model development

• Data-driven prediction (e.g., neural networks, Gaussian processes

• Experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn.

• Hands-on experience integrating AI models with traditional solvers to create hybrid simulation workflows.
• Experience with HPC clusters, parallel solvers (MPI/OpenMP), and job schedulers.
• UDFs, custom solver extensions, or code-level customization in OpenFOAM/Fluent/Abaqus

Consulting Competencies

• Strong ability to diagnose client needs and propose the right simulation or AI-based solutions.
• Capable of managing multiple projects and delivering high-quality results within deadlines.
• Excellent communication skills, including client-facing discussions and technical presentations.
• Ability to translate complex simulation outcomes into clear, actionable engineering guidance.
• Independent, proactive, and innovation-focused mindset.

Industry Experience

• Manufacturing
• Automotive & EV
• Electronics & Semiconductor
• Aerospace & Defense
• Energy, Renewables, Thermal Systems
• Chemical Process, Oil & Gas
• Biomedical Engineering
  Consumer Products & Industrial Engineering

Engagement Model

• Contract / Consulting / Project-based
• Remote, onsite, or hybrid support depending on client needs
• Engagement may include short-term simulation tasks, long-term R&D support, or multi-disciplinary innovation projects.